
"""simple docstring"""






# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import argparse
import os

from accelerate.test_utils import execute_subprocess_async




def __magic_name__	(				_lowerCamelCase:		Union[str, Any]=None			)					->						Optional[Any]:

	'''simple docstring'''




	if subparsers is not None:
		lowerCAmelCase												=  subparsers.add_parser('''test'''			)
	else:
		lowerCAmelCase												=  argparse.ArgumentParser('''Accelerate test command'''			)

	parser.add_argument(
	    '''--config_file''',					default=_lowerCamelCase,					help=(
	        '''The path to use to store the config file. Will default to a file named default_config.yaml in the cache '''
	        '''location, which is the content of the environment `HF_HOME` suffixed with \'accelerate\', or if you don\'t have '''
	        '''such an environment variable, your cache directory (\'~/.cache\' or the content of `XDG_CACHE_HOME`) suffixed '''
	        '''with \'huggingface\'.'''
	    ),					)

	if subparsers is not None:
		parser.set_defaults(func=_lowerCamelCase			)
	return parser




def __magic_name__	(				_lowerCamelCase:		List[Any]			)					->						Union[str, Any]:

	'''simple docstring'''




	lowerCAmelCase												=  os.path.sep.join(__file__.split(os.path.sep			)[:-2] + ['''test_utils''', '''scripts''', '''test_script.py''']			)

	if args.config_file is None:
		lowerCAmelCase												=  script_name
	else:
		lowerCAmelCase												=  F"""--config_file={args.config_file} {script_name}"""

	lowerCAmelCase												=  ['''accelerate-launch'''] + test_args.split()
	lowerCAmelCase												=  execute_subprocess_async(_lowerCamelCase,					env=os.environ.copy()			)
	if result.returncode == 0:
		print('''Test is a success! You are ready for your distributed training!'''			)




def __magic_name__	(				)					->						int:

	'''simple docstring'''




	lowerCAmelCase												=  test_command_parser()
	lowerCAmelCase												=  parser.parse_args()
	test_command(_lowerCamelCase			)


if __name__ == "__main__":
					main()




"""simple docstring"""






import tempfile
import unittest

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
    is_torch_available,
    require_optimum,
    require_torch,
    slow,
)


if is_torch_available():
					import torch



@require_torch
@require_optimum
@slow
class 			lowercase					( unittest.TestCase		):






			def 					UpperCAmelCase							(self  :	Tuple			)       ->	Optional[int]:





				"""simple docstring"""


				lowerCAmelCase												=  '''hf-internal-testing/tiny-random-t5'''
				lowerCAmelCase												=  AutoTokenizer.from_pretrained(SCREAMING_SNAKE_CASE_			)
				lowerCAmelCase												=  AutoModelForSeqaSeqLM.from_pretrained(SCREAMING_SNAKE_CASE_			)

				lowerCAmelCase												=  tokenizer('''This is me'''      ,return_tensors='''pt'''			)

				lowerCAmelCase												=  model.to_bettertransformer()

				self.assertTrue(any('''BetterTransformer''' in mod.__class__.__name__ for _, mod in model.named_modules()			)			)

				lowerCAmelCase												=  model.generate(**SCREAMING_SNAKE_CASE_			)

				lowerCAmelCase												=  model.reverse_bettertransformer()

				self.assertFalse(any('''BetterTransformer''' in mod.__class__.__name__ for _, mod in model.named_modules()			)			)

				with tempfile.TemporaryDirectory() as tmpdirname:
					model.save_pretrained(SCREAMING_SNAKE_CASE_			)

					lowerCAmelCase												=  AutoModelForSeqaSeqLM.from_pretrained(SCREAMING_SNAKE_CASE_			)

					self.assertFalse(
					    any('''BetterTransformer''' in mod.__class__.__name__ for _, mod in model_reloaded.named_modules()			)			)

					lowerCAmelCase												=  model_reloaded.generate(**SCREAMING_SNAKE_CASE_			)
					self.assertTrue(torch.allclose(SCREAMING_SNAKE_CASE_      ,SCREAMING_SNAKE_CASE_			)			)






			def 					UpperCAmelCase							(self  :	str			)       ->	Tuple:





				"""simple docstring"""


				lowerCAmelCase												=  '''hf-internal-testing/tiny-random-t5'''
				lowerCAmelCase												=  AutoModelForSeqaSeqLM.from_pretrained(SCREAMING_SNAKE_CASE_			)

				lowerCAmelCase												=  model.to_bettertransformer()

				with tempfile.TemporaryDirectory() as tmpdirname:
					with self.assertRaises(SCREAMING_SNAKE_CASE_			):
						model.save_pretrained(SCREAMING_SNAKE_CASE_			)

					lowerCAmelCase												=  model.reverse_bettertransformer()
					model.save_pretrained(SCREAMING_SNAKE_CASE_			)


